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Bayesian Inferential Reasoning Model for Crime Investigation

Wang, Jing and Xu, Zhijie (2014) Bayesian Inferential Reasoning Model for Crime Investigation. In: 6th International Conference on Intelligent Decision Technologies, 18-20 June 2014, Chania, Greece. (In Press)

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Abstract

Forensic inferential reasoning is a “fact-finding” journey for crime investigation and evidence presentation. In complex legal practices involving various forms of evidence, conventional decision making processes based on human intuition and piece-to-piece evidence explanation often fail to reconstruct meaningful and convincing legal hypothesis. It is necessary to develop logical system for evidence management and relationship evaluations. In this paper, a forensic application-oriented inferential reasoning model has been devised base on Bayesian Networks. It provides an effective approach to identify and evaluate possible relationships among different evidence. The model has been developed into an adaptive framework than can be further extended to support information visualisation and interaction. Based on the system experiments, the model has been successfully used in verifying the logical relationships between DNA testing results and confessions acquired from the suspect in a simulated criminal investigation, which provided a firm foundation for the future developments.

Item Type: Conference or Workshop Item (Paper)
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Schools: School of Computing and Engineering > High-Performance Intelligent Computing
School of Computing and Engineering
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Depositing User: Jing Wang
Date Deposited: 02 Jun 2014 12:06
Last Modified: 06 Nov 2015 04:46
URI: http://eprints.hud.ac.uk/id/eprint/20384

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